I read 21 articles, watched 7 videos, listened to 4 podcasts and tried 12 tools. Here’s the AI Marketing stuff you should really 🧠 KNOW, 👀 SEE and 🧪 TRY as a mortal marketeer.

Things to Know 🧠

Spicy stats and facts to drop in your next marketing meeting

🧠 Your 2019 SEO playbook is officially a paperweight. HBR just confirmed the two-front war on your career. Search is shifting from keyword matching to intent-based chat. Here’s the thing: “brand awareness” now means securing placement in LLM training data. AI agents are taking over the research phase, leaving humans to only handle the final “buy” button. If a bot does the shopping, your flashy landing page is basically shouting into a void. Cool. Read the full article on the two-front AI war

🧠 Prompting is officially a legacy skill. If your 2026 strategy is still “copy-pasting from ChatGPT,” you’re basically using a digital typewriter. The new guard of AI agents—like Agentforce and Breeze—have moved past ‘creative assistants’ and into ‘execution partners.’ They live inside your CRM, trigger campaigns, and handle the UNGODLY amount of data-heavy tasks like lead scoring while you’re at lunch. Content is a commodity; the real flex is autonomous execution that actually closes deals. Read the full roundup of 2026’s best AI agents

Things to See 👀

Content you’ll read instead of hoarding it in the tab graveyard

👀 Stop being an AI Overview victim — keyword research for the post-GPT search era (Video by Ahrefs)

• Apply the 10-second rule: If a bot can answer the query in under 10 seconds, stop trying to rank for it. Here’s the thing: you’ve already lost.

• AI Overviews don’t care about your “classic” SEO tricks. Optimize for the direct answer first or accept your fate as a clickless ghost.

• Discovery is dead. Your content needs to be the final destination for users who actually need more than a bot’s mediocre summary.

👀 From 300 views to 85k: Eric Siu’s OpenClaw setup for viral X content (Video by Eric Siu)

• Stop posting based on “vibes” (I feel attacked). Eric switched to a rigid AI-structured framework and his views 200x’d while I’m still refreshing my 358-view post.

• AI writes better hooks than you. Use structured, receipt-based prompts that LLMs can actually replicate without the usual “delve” and “unveil” garbage.

• Visual logic wins. Feeding AI your diagrams to create long-form social content drives more inbound subscribers than your best manual writing ever will.

👀 Claude is not a chatbot, it’s your new marketing IDE (Video by Greg Isenberg & James Dickerson)

• Look: stop treating Claude like a magic 8-ball. It’s an IDE for your marketing. If you’re still copy-pasting single prompts into a chat window, you’re basically playing with a very expensive Tamagotchi.

• Chat histories are where productivity goes to die. Real growth requires persistent logic and code-backed workflows that don’t “forget” the context. Build machines, not conversations.

• High-impact marketing is usually boring as f*ck. James shows how to automate the repetitive tasks you’re currently “too busy” to fix. 60 minutes of setup saves an UNGODLY amount of time later.

Things to Try 🧪

Tools that make you look like a genius before the others catch up

🧪 Sparkles: Stop begging developers to fix your typos and just ship the PR yourself (Free tier available)

• Turn visual site edits into actual GitHub pull requests so you can stop being a “backlog item” and start being a person who actually ships stuff.

• Kill the “it’s on the roadmap” excuse for simple copy tweaks or design fixes that take two minutes but usually wait two weeks.

• Connects to your existing repo so you can edit production code via a visual UI without having to learn what a “terminal” is.

🧪 Lunair: Stop paying agencies $5k for explainer videos that look like generic insurance ads (Free tier capped at 20s / Paid for longer clips)

• Finally solves the “AI fever dream” problem with actual character consistency across scenes. No more protagonists growing extra limbs halfway through your demo.

• Edit the script, music, and narrator using plain English. It’s like having a very patient intern who doesn’t complain when you change your mind for the fourth time.

• The 20-second free limit is a blessing in disguise. It forces you to be punchy instead of making that 5-minute “brand manifesto” literally nobody was going to watch anyway.

🧪 ChatWithAds: Stop playing Spreadsheet Tetris and just ask your data why your ads are failing (Free to try / Paid)

• Talk to your Meta and Google Ads data in plain English because (let’s be real) nobody actually enjoys pivot tables.

• Ditch the crapload of tabs in that dashboard your agency built and you haven’t opened since Q3.

• Get immediate, actionable answers on which campaigns are actually driving revenue and which ones are just burning cash.

That’s it. You’re now caught up on AI + marketing. One step closer to becoming truly AI-powered. No doomscrolling required.

Cheers,

Kasper, The Artificial Marketeer

This week: hard proof that AI-generated ads match human ones (if you follow one weird trick), Jasper’s state of AI report that basically eulogizes your content volume strategy, and why YouTube just became the most important SEO channel you’re ignoring.

I read 27 articles, watched 13 videos, listened to 5 podcasts and tried 8 tools. Here’s the stuff you should really 🧠 KNOW, 👀 SEE and 🧪 TRY as a mortal marketeer.

Things to Know 🧠

Spicy stats and facts to drop in your next marketing meeting

🧠 AI ads match human-made ads. But only if they don’t look AI-made. Taboola, Columbia, Harvard, and Carnegie Mellon analyzed 500M+ impressions. AI ads hit 0.76% CTR vs 0.65% for humans. The catch: nearly half of AI ads were perceived as human-made, and those outperformed everything. The strongest signal? Large, clear human faces. Not polished renders. Not saturated colors. Actual faces. The more “AI” it looked, the worse it performed. Your move: stop making AI creative look like AI creative. Read the full breakdown

🧠 Your “content volume” strategy is officially dead. Jasper’s 2026 State of AI in Marketing report is out, and it’s basically a eulogy for the “publish more” playbook. Early AI adopters are crushing laggards. Not because they produce more content, but because they produce better content faster and spend the saved time on strategy. The report is packed with data on how the top teams actually use AI. Spoiler: it’s not “write me a blog post.” Read the full Jasper report (PDF)

🧠 AI chatbots now cite YouTube more than Reddit. If your SEO strategy is still “write articles and pray,” you’re becoming invisible to the models your customers actually use. AI systems have shifted their sourcing preference to video. YouTube is now the go-to reference for AI-generated answers. No video strategy? You’re not just missing traffic. You’re missing citations. Read the full analysis on Tubefilter

Things to See 👀

Content you’ll read instead of hoarding it in the tab graveyard

👀 How AI is changing marketing attribution: finally prove your marketing works (Article by Carilu Dietrich)

• AI spots patterns in the buyer journey that traditional last-touch attribution completely misses

• Visualize complex multi-touch paths so you can stop guessing which channels actually drive revenue

• The old “who gets credit” wars between marketing and sales are about to get settled by a robot. Progress.

👀 MKT1 unboxes Luma AI to see if it’s actually useful or just another AI hallucination factory (Video by Emily Kramer)

• Real-world marketing asset test: can Luma produce usable creative or just pretty garbage?

• Emily’s no-BS format means you get the verdict in 30 minutes instead of reading 12 reviews that all say “it depends”

• If you’re evaluating AI creative tools, this saves you the trial-and-error. She already did it

👀 How to extract and map Gemini 3 fan-out queries before your traffic evaporates (Guide by Chris Long / Nectiv Digital)

• Gemini 3 generates 4x more related queries than ChatGPT (avg 10.7 per prompt, up 78% from Gemini 2.5). Each one is a content gap you’re probably not covering

• Step-by-step: use the Gemini API to extract “webSearchQueries,” then map them against your existing pages with a domain coverage analyzer

• Stop optimizing for single keywords. AI search fans out into long-tail clusters. Cover them or your competitor will

Things to Try 🧪

Tools that make you look like a genius before the others catch up

🧪 Extrovert: Stop cold DMing. Start warm lurking. AI-powered LinkedIn engagement that doesn’t make you look like a bot. ($29-75/mo)

• Tracks your prospects’ LinkedIn posts and suggests smart comments and DMs based on your playbook

• Keeps nurturing running on autopilot. Unlike email drip sequences, this one doesn’t stop after 5 emails and give up

• Connects to HubSpot, Clay, Lemlist, and Zapier. So your CRM actually knows what your LinkedIn is doing

🧪 Relay.app: Build AI workflows between your tools without learning to code or begging a developer. (Free tier with 200 steps/mo, then $19/mo)

• AI agents that handle the boring middle-man work between HubSpot, Slack, Notion, and your inbox

• Paths with conditional logic: let AI decide which workflow branch to follow, or flag a human when it’s unsure

• Built-in AI credits for GPT-4o, Claude, and Gemini. No separate API keys needed

🧪 findable.: Check if ChatGPT, Claude, and Perplexity even know your brand exists. Then fix it. (Free)

• Tracks your brand mentions across AI answer engines so you know who’s recommending you and who’s ghosting you

• Compares your AI visibility against competitors. The new “share of voice” is “share of model”

• Free tier actually works. No credit card bait-and-switch. Just plug in your brand and see where you stand

That’s it. You’re now caught up on AI + marketing. Your brand is being auditioned by robots whether you like it or not. Might as well show up prepared. Now go close those 47 browser tabs you were “definitely going to read later.”

Cheers,

Kasper, The Artificial Marketeer

But back in the real world, you still have targets to hit and a boss asking what AI actually changes for marketing. Let’s get into it.

I read 18 articles, watched 8 videos, listened to 5 podcasts and tried 7 tools. Here’s the stuff you should really 🧠 KNOW, 👀 SEE and 🧪 TRY as a mortal marketeer.

Things to Know

Spicy stats and facts to drop in your next marketing meeting

🧠 Your “ad-free” AI honeymoon is over. OpenAI is building ad infrastructure. Not banners inside ChatGPT: “Agent Ads.” Brand placements and suggested actions baked into the AI’s reasoning chain. You won’t market to humans scrolling a feed. You’ll market to the bot that decides what humans see.

Read the full breakdown on monetizing AI surfaces

🧠 Your automation workflows have an expiration date. Agentic AI doesn’t follow instructions. It sets its own agenda, picks its own actions, and pivots in real-time to hit KPIs. The market: $2.4B today, $65B by 2034. Your manual campaign management just got a countdown clock.

Read the full analysis on agentic AI vs. traditional automation

🧠 LLMs are masters of “vibes” and terrible at reality. AI produces tone, consensus, and general wisdom all day. What it can’t do: cite specific numbers, real scenarios, and artifacts that prove you’re not a bot. The antidote: anchor every claim with hard-to-fake facts.

Read the full SparkToro essay on vibes vs. facts

Things to See

Content you’ll read instead of hoarding it in the tab graveyard

👀 AI agent does your Reddit research so you can stop doomscrolling for insights (Video by Claire Vo)

• AI agents with browser access can now autonomously navigate Reddit, extract customer pain points, and synthesize audience sentiment

• The shift from “chatting with a bot” to “assigning it a research mission” is the real productivity leap for market research

• Watch the full workflow: from giving the agent a brief to getting structured, actionable audience data back in minutes

👀 Five SEO heavyweights break down Generative Engine Optimization: the strategy Google can’t teach you yet (Video by Ahrefs)

• GEO requires “signal-planting” that LLMs can verify. Not keyword-stuffing for crawlers. Completely different skill set.

• Optimize for conversational intent behind prompts, not the static 2-3 word queries we’ve relied on for a decade

• Brand authority in AI search is earned through specific citation signals that prove your content is the most reliable answer

👀 The Gen Marketer Summit recap: what OpenAI, Clay, and Profound told B2B teams (Article by MKT1)

• The marketer’s role is shifting from “specialist who produces” to “orchestrator who directs AI systems”

• Programmatic outbound is the new baseline: Clay-style AI enrichment is killing generic cold outreach

• Content moats are moving from volume to earned trust. AI generates “good” content instantly. Your edge: unique data and real community.

Things to Try

Tools that make you look like a genius before the others catch up

🧪 Prospera AI: LinkedIn outreach on autopilot. Without sounding like every other “I see you work at [Company]” DM.

(Paid, free trial available)

• Full-funnel LinkedIn automation: lead discovery to personalized DMs

• AI-generated messaging that actually references context

• Focused on doubling sales calls, not vanity “messages sent” stats

🧪 Leapility: Turn repetitive marketing tasks into AI playbooks. Describe in plain English, hit run.

(Free to start)

• Done a task three times this week? Make it a playbook instead

• Add your own rules and data sources for on-brand output

• No code, no Zapier. Just plain language workflows

🧪 Aura: Generate real UI from a text prompt. Export to Figma or HTML.

(Free tier available)

• Functional layouts and animations, not just static mockups

• Brief to landing page design in seconds. No blank canvas phase

• Clean code export. Skip the devs or make them happy

That’s it. You’re now caught up on AI + marketing. The bots are buying ads, running campaigns, and doing your Reddit research. At least you still have to hit “publish.”

Cheers,

Kasper, The Artificial Marketeer

Both are probably right. Synthetic users are garbage for replacing real conversations, but might be gold for pre-testing messaging before you burn $50k. You decide who’s full of shit.

I read 33 articles, watched 16 videos, listened to 9 podcasts and tried 8 tools. Here’s the stuff you should really 🧠 KNOW, 👀 SEE and 🧪 TRY as a mortal marketeer.

Things to know

Spicy stats and facts to drop in your next marketing meeting

🧠 Your “content moat” just evaporated. AI turned “good enough” content into a free commodity. If your strategy is still “produce more blog posts than the competition,” you’re already dead.
Read the full breakdown on the three new marketing advantages

🧠 AI “synthetic users” are just expensive confirmation bias. Founders would rather talk to a bot than a real customer. Problem is: AI personas are programmed to be predictable (the literal opposite of how humans behave).
Read the full takedown on why AI personas are a trap

🧠 The “SEO Guy” and “Email Girl” are officially on the endangered species list. AI just nuked the execution floor. One “Gen Marketer” can now replace a 5-person specialist team by focusing on strategy while the bots handle the grunt work.
Read the full essay on the rise of the Gen Marketer

Things to see

Content you’ll read instead of hoarding it in the tab graveyard

👀 49 AI Marketing Examples — actual workflows, not theoretical garbage (Article by PeerSignal)

• Forget “one-click miracles.” Focus on modular tasks like SEO keyword clustering or competitor audits at scale

• Stop using single prompts. Chain tools together to kill dozens of hours of manual research

• Copy-paste ready. No theory, just steal and ship

👀 How to build B2B video ads that don’t suck — for the price of a few API calls (Video by Shlomo Genchin)

• Use Perplexity to scrape customer pain points before you touch a single video tool

• Apply the TPSA formula (Tension, Problem, Solution, Action) to make AI voiceovers sound human

• Combine Gemini for keyframes + Kling for footage. DIY budget, agency-level creative

👀 A 90-day SEO playbook for AI-driven search visibility (Guide by Search Engine Land)

• Flip your content hierarchy. Put the direct answer at the top so the LLM doesn’t have to dig

• Overdose on Schema markup. Structured data is digital crack for bots

• Beef up E-E-A-T signals. Expert bios and citations are your only shield against being flagged as a hallucination risk

Things to try

Tools that make you look like a genius before the others catch up

🧪 Amplitude AI Visibility Report: Find out if ChatGPT even knows your brand exists
(Free)

• Track your “Share of Model” to see which LLMs cite you and which ones are ghosting you

• Identify queries where AI-generated answers are stealing your traffic or boosting your brand

• Get a concrete baseline for AI Search Optimization before your competitors do

🧪 Fimo: Build a website in the time it takes to explain your brief to a dev who isn’t listening
(Free to try)

• 10-second prompt → live site. No more staring at a blank Figma file

• It’s a “living” CMS workspace. You and the AI keep evolving the site after launch

• Ship landing pages before your coffee—or the campaign idea—gets cold

🧪 atypica.AI: Simulate 1,000 customer interviews in minutes. Yes, the tool that contradicts the article above.
(Free demo)

• Builds synthetic personas and grills them to find emotional triggers that surveys miss

• Uses “narrative economics” to test how your messaging lands with different cognitive profiles

• Use it as a pre-flight check before you burn budget—then talk to real humans. Both camps win.

That’s it. You’re now caught up on AI + marketing. One step closer to becoming an Artificial Marketeer. No doomscrolling required.

Cheers,

Kasper, The Artificial Marketeer

This is prediction #4/15 for marketing careers:

I’ve developed a new kind of banner blindness.

Not for ads. For AI slop.

@cutebaby_ai2Hello mama hello😂😂@PixVerse #pixverse #pixverse #papa #viralvideos #100k

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I love both babies and kittens, but my god this is just trailer trash. And it has 8M views…

I skip obviously AI-generated videos instantly. I scroll past obvious AI-generated LinkedIn posts without reading them. I unsubscribed from newsletters that sounded like ChatGPT with a corporate filter. I close browser tabs the moment I land on a site that feels like every other template Lovable site.

My attention is only triggered by captivating stuff. Whether they used AI or not doesn’t really matter. What matters is whether it feels like someone actually put in the effort to create something worth my time.

I might be biased. I work in marketing. But I don’t think I’m alone.

Prediction 4/15: The “Human Premium” emerges. Do you need to become anti-AI?

What’s happening? The internet drowned in synthetic noise.

You’ve seen the typical stats: like “90% of online content will be AI-generated” or “more than half of internet traffic is bots”.

The dead internet theory, basically.

The result? What the internet calls “AI slop”. Low-effort synthetic content designed to game algorithms. Parrot-on-a-bike videos. AI Stephen Hawking explaining crypto. Talking babies everywhere. LinkedIn thought leadership that reads like it was generated by a prompt that included the word “leadership.”

And consumers are reacting.

Research from Washington State University found that labeling content as “Made with AI” can actually lower purchase intention and emotional trust. Consumers perceive AI-generated marketing as “effortless” and “lazy.”

That’s not a tech problem. That’s a brand problem.

Kieran Flanagan, SVP of Marketing at HubSpot:

“The more content is generated by AI, the more I think people will switch towards trusting content from someone they trust like an individual versus a brand.”

Faces beat logos. Personal beats corporate. Human beats synthetic.

The “Human Premium” isn’t anti-technology. It’s anti-average.

What’s amplifying this? AI defaults to the mean. Humans provide the variance.

Here’s the research that should worry every marketer leaning too hard on AI for creative work.

Jessica Apotheker, CMO at BCG, shared findings from a Harvard/BCG study:

“When people over-rely on generative AI, the collective divergence of ideas drops by 40 percent. Concretely, that means that new ideas don’t come to the surface. It means that true innovation is being stifled.”

Why? Because AI was trained on existing content. It produces pattern replication at scale. As Alicia Arnold puts it:

“What AI produces is not creativity, it’s pattern replication at scale... It can’t understand the cultural tension that makes a message land powerfully or fall flat.”

The result is what Kantar’s Mary Kyriakidi calls the “sea of sameness”:

“Brands that fail to differentiate risk being lost in a sea of sameness—if you’re not the default recommendation, you’ll be optimised out.”

Everyone’s using the same tools. The same prompts. Getting the same outputs.

And audiences are tuning out.

The brands winning aren’t the ones publishing more AI content. They’re the ones publishing different content.

The case studies that prove it

Dove pledged to never use AI to create or distort women’s images. They released a “Real Beauty Prompt Playbook” to counter the synthetic tide. By opting out of the AI race in visual representation, they reinforced their core equity: authenticity.

Lush Cosmetics went further. They quit social media entirely: Meta, TikTok, all of it. To create what they call a “walled garden” of safer community. Instead of algorithmic reach, they invested in physical events and creator partnerships.

Conventional wisdom says quitting social is suicide. But Lush reported its best December sales in two years and a 54% increase in physical store sales.

But you don’t need to ban AI or quit socials to be different.

Kalshi, the prediction market, took the complete opposite approach. They leaned into AI-generated marketing—but made it so obviously, intentionally weird that it became distinctive. They stayed away from the uncanny valley by embracing the absurdity. Obvious AI, but with a point of view.

Compare that to Coca-Cola’s AI-generated Christmas campaign or McDonald’s rejected AI ad in the Netherlands. Both got torched because they hit the uncanny valley dead center (and lots of other reasons). Close to real, but off.

The lesson isn’t “don’t use AI.” It’s “don’t be boring with it.”

What’s the catch? Leadership is squeezing the wrong way.

Here’s where I pump the brakes on the “Human Premium” hype. Because there’s a painful tension nobody’s addressing.

The consumer wants human. They’re tuning out AI slop, craving authenticity, rewarding brands that feel real. Authenticity creates premium.

But leadership wants efficiency. “Can’t we do that with AI?” is now a standard question in board meetings and marketing reviews.

Every marketing team is getting squeezed. Less budget. Less headcount. More pressure to automate.

The result? The people who could add the human premium are being pushed to produce more AI slop instead.

This hits small businesses hardest. Big brands like Dove and Lush have the equity and budget to make bold “human-first” bets. A 10-person startup doesn’t have the luxury of quitting social media to prove a point.

And let me be clear: “Human Premium” doesn’t mean “anti-AI.”

I don’t believe in being anti-AI. That’s like being anti-electricity in 1830. AI is useful progression, if used right.

The problem isn’t AI. The problem is lazy AI.

Copy-paste prompts. Zero editing. No human judgment in the loop.

Consumers don’t care if you prompted Claude at 2am to help write your newsletter. They care if the newsletter is interesting, relevant, fun...

The winning formula isn’t Human vs. AI. It’s Human + AI, with the human providing the taste, judgment, and creative direction that AI can’t.

That’s what I mean with the banner blindness. My attention only triggers for content that feels like someone gave a shit.

Whether they used AI to make it? I genuinely don’t care. What I care about is whether it’s interesting.

The storyteller signal

Here’s a trend that caught my attention. The Wall Street Journal reported that companies are increasingly hiring for roles explicitly called “storyteller.”

Not novelists. Not content managers with a fancy title.

But people who can translate complexity, restore trust, and make meaning in noisy, AI-saturated systems.

LinkedIn data shows the percentage of US job postings including the term “storyteller” doubled in the year ended November 2025. Over 50,000 marketing listings. More than 20,000 in media and communications.

That’s the market signaling what it needs: humans who can make sense of the chaos.

What to do if you’re just starting in marketing?

Here’s the uncomfortable truth for new marketers: AI is automating the grunt work that used to teach you taste.

Junior marketers learned by writing dozens of social posts, pulling reports manually, making mistakes on low-stakes projects. That middle layer is being hollowed out.

So how do you develop taste if AI does the reps for you?

1. Study the outliers. Build a swipe file of marketing that moved you. Not what got engagement. What actually made you stop, think, feel something. Train your eye for distinctiveness.

2. Edit AI output ruthlessly. Use AI as a starting point, then tear it apart. The editing is the education. Every “this sounds generic” moment is a lesson.

3. Develop opinions. AI has no opinions. It produces the average of the internet. Your opinions, your taste, your point of view. That’s your competitive moat.

So what now? Be the Purple Cow in the sea of sameness.

Here’s the practical starting point for any marketing manager:

1. Ask the Purple Cow question.

What is everyone else doing (zigging)? How can you be remarkable (zagging)?

This isn’t new thinking. Seth Godin wrote Purple Cow in 2003. But it’s never been more relevant. When everyone has the same AI tools, differentiation becomes the only game.

For those that need a reminder:

2. Audit your content for “slop signals.”

Be honest: does your content look like AI generated it? Same structure, same phrases, same stock-image-energy visuals?

If you can’t tell your content from a competitor’s, neither can your audience.

3. Invest in faces, not just logos.

The data shows audiences trust individuals over brands:

→ Founder-led content outperforms corporate content

→ Personal LinkedIn profiles get 4-5x more reach than company pages

→ YouTube channels with faces grow 3x faster than faceless YouTube channels

Where can you put more humans in front of your brand? More video with real people? More podcast appearances? More founder visibility?

4. Use AI to scale your voice, not to replace it.

The winning workflow: Capture your raw human thoughts (voice memos, interviews, rants). Use AI to format and scale those thoughts. Edit with your judgment.

The human premium isn’t about avoiding AI. It’s about ensuring the human stays in the driver’s seat.

One of my favorite examples of last year: Hubspot’s “Marketing Against the Grain” YouTube Channel. They’re using tons of AI solutons to brainstorm, create, edit and distribute the video. But it’s still 100% human.

5. Embrace unscalable authenticity.

Not everything. Not always. But identify the moments where human touch matters most. First impressions. Key conversions. Community building.

Like the epic “do things that don’t scale” essay from Y Combinator founder Paul Graham.

Then protect those moments from automation pressure.

That’s it for this prediction. Agree/disagree? Got remarks? Roast me in the comments.

Leave a comment

What’s next? Time becomes a liability.

Tomorrow: Prediction #5 — “Taking your time” becomes a career risk.

Spoiler: The marketer who loved spending 8 hours perfecting a blog post? They’re now a liability. AI reset the market’s expectations. And the friction between AI-native and AI-curious teammates is creating real tension.

Cheers, Kasper

This is prediction #3/15 for marketing careers.

A few weeks ago I was looking for DJ gear. My dad just retired and wanted to learn DJing (hello late-life crisis). As a student, I used to be a not-so-great DJ. I still kinda know how it works, but my gear knowledge was 10+ years out of date.

So I opened Gemini, gave it some criteria and hit the deep research button. After about 10 minutes I got two clear winners with a nice comparison table and clear, structured argumentation. Gemini answered follow-up questions about tech specs, searched Reddit and forums for real user reviews. I asked it to find the cheapest place to buy the chosen device and it gave me one with a nice 29% discount. NICE.

15 minutes. Never opened Google. Never visited a brand website. Didn’t compare ecommerce sites. The AI did my entire purchase journey: research, comparison, community validation, price shopping. My personal shopping assistant.

The customer journey just got a co-pilot. And soon, the co-pilot will be flying the plane.

Prediction 3/15: AI becomes the new gatekeeper. If the model doesn’t know you, it won’t choose you.

What’s happening? You’re marketing to two audiences now.

Here’s the number: 24% of consumers already use an AI-powered shopping assistant.

That’s one in four customers potentially asking an AI what to buy before they ever visit your website.

We’re moving from AI as assistant to AI as agent.

But here’s what most marketers miss: these AI agents don’t experience your brand the way humans do. They don’t see your logo. They don’t feel your vibe. They don’t watch your brand video.

They parse your data.

And if that data isn’t structured in a way they can read? You’re invisible.

The terminology is evolving fast and nobody agrees on abbreviations and terms. But I like to compare it this way:

GEO (Generative Engine Optimization)

Optimizing so AI search engines can find and recommend you (what we covered in Prediction #2).

AEO (Agent Engine Optimization)

The next evolution, optimizing for AI agents that act autonomously on behalf of consumers.

Yeah I know some people use AEO for “Answer Engine Optimization” which is basically the same as GEO imho. I totally hate Gartner but they also use AEO like this so yeah. ¯\_(ツ)_/¯

Schema markup, JSON-LD

The technical infrastructure that makes you machine-readable.

You better keep up.

You thought you were optimizing for Google. Then for ChatGPT. Now for AI agents that book, buy, and negotiate without human approval.

You’re not just marketing to humans anymore. You’re marketing to the machines that influence humans. And increasingly, those machines have opinions.

What’s amplifying this? AI agents read differently than humans.

Here’s what clicked for me: humans and AI agents process information completely differently.

How humans read your site:

1. Land on homepage

2. Get a vibe from design and messaging

3. Browse around, click what looks interesting

4. Read testimonials, watch videos, compare items

5. Eventually find pricing and specs

6. Decide based on feeling + logic

How AI agents read your site:

1. Parse structured data (JSON-LD, Schema markup)

2. Extract: price, availability, features, ratings

3. Compare against user criteria

4. Recommend or skip

5. Never see your beautiful homepage

The agent journey is clinical. It’s comparison shopping on steroids. And it happens before the human even knows options exist.

Marketers have always talked about customer journeys. Now there are two:

Journey 1: The Human Journey

The buyer researches, compares, reads reviews, asks friends, decides. You know this one. You’ve optimized for it your whole career.

Journey 2: The Agent Journey

The AI assistant researches, filters, compares specs, checks availability, and recommends. Sometimes before the human even knows they’re shopping.

Keron Rose calls this “Delegated Intent.” Consumers aren’t searching anymore. They’re assigning missions: “Find me white sneakers under $120 that match my wardrobe. Find the best option and buy it.”

And the infrastructure is already being built. Shopify rolled out “Universal Cart” functionality. AI agents can now lump items from multiple stores into one cart and execute a single checkout. The consumer never visits your website.

Here’s the uncomfortable part: these journeys can happen simultaneously. Or the agent journey can happen instead of the human journey.

When your customer says “find me the best project management tool under $20/month,” they’re not opening 15 browser tabs anymore. The AI does the filtering. The AI makes the shortlist. The human just approves.

If you’re not on that shortlist, you never existed.

The shift is already measurable:

• AI traffic to retail sites is up 805% year-over-year. (Adobe)

• $14.2 billion in global online sales were driven by AI agents in 2024. (Salesforce)

• By 2028 90% of B2B buying interactions will be intermediated by AI agents. (Gartner)

This isn’t future speculation. It’s happening now.

What’s the catch? The agents are still dumb (for now).

Before you panic about robot overlords choosing your customers’ purchases, let’s inject some reality.

“Agent” is generous terminology.

Right now, most “AI shopping assistants” are glorified search with better summarization. They’re not autonomously purchasing. They’re not negotiating prices. They’re not managing ongoing vendor relationships.

The fully agentic behavior exists but is edge-case. The tech still needs to advance before AI books, buys, cancels, and negotiates without human approval.

The agent economy is still tiny.

Yes, 24% of consumers use AI shopping assistants. But “use” doesn’t mean “delegate all purchase decisions to.” Most people are still using AI for research, not for buying. The fully autonomous purchase is still rare.

We’re still using AI as a shopping research assistant for now.

But not even 3 years ago (!!!) we were laughing with Will Smith eating spaghetti. Who’s laughing now?

The “black box” problem got worse.

In Prediction #2, I mentioned you can’t easily track AI search visibility. With AI agents, it’s even murkier. How do you know which agents are recommending you? How do you measure “agent awareness”?

Right now, you can’t. Not reliably. You’re optimizing based on theory and spot-checks.

Nobody knows what “optimizing for agents” actually means.

The honest truth: AEO is still mostly vapor. The consultants selling it don’t have playbooks yet. They’re figuring it out as they go. Anyone who claims to have cracked the code is probably overselling.

What we do know: machine-readability matters. Structured data matters. Being mentioned in trusted sources matters (hello, GEO from yesterday). Beyond that? It’s educated guessing.

AI agents have a Big Brand Bias.

Here’s research that should scare challenger brands: University of Toronto tested how AI recommends products. When queries were unbranded (”suggest a good soda”), ChatGPT favored major global brands 56.3% of the time. Perplexity? 67.9%. Niche brands were cited as low as 5.8% of the time.

The models learned from internet data. Internet data over-represents big brands. So the AI defaults to Coke, not your craft cola.

Here’s how dominant that bias is: Heinz ran an experiment with DALL-E 2. They prompted the AI with generic terms like “ketchup,” “ketchup art,” “ketchup in space”… without mentioning the brand. The AI overwhelmingly generated images that looked exactly like Heinz bottles. The model learned: ketchup = Heinz. That’s “Share of Model.”

University of Toronto also found that for high-stakes purchases (like cars), AI search serves 81.9% earned media (reviews, news) vs only 18% brand content. Compare that to Google’s 45%/40% split. AI actively suppresses brand-owned content in favor of third-party validation.

If you’re a challenger brand, you can’t rely on generic recommendations. You need “Justification Attributes”: specific, extractable data points (”100% organic,” “lifetime warranty,” “made in Belgium”) that give the AI a logical reason to choose you over the default giant.

The human still signs the check.

Even when AI agents recommend and filter, a human usually approves the final purchase. That means brand trust, emotional connection, and differentiation still matter. The agent gets you on the shortlist. The human makes the final call.

Don’t abandon human-focused marketing. Just add a new layer.

What to do if you’re just starting in marketing?

Here’s the practical reality: you probably don’t need to specialize in AEO right now. It’s too early, too undefined, and too niche.

But you should understand the direction things are heading.

The skill that will matter: understanding how machines read and process information.

This means learning:

• How structured data works (Schema.org, JSON-LD)

• How AI agents retrieve and compare information

• How to write content that’s both human-readable AND machine-parseable

The marketers who’ll thrive in 5 years understand both human psychology AND machine parsing. They speak to hearts AND data structures.

Also: everything from yesterday’s prediction (GEO) applies here. Getting mentioned in trusted sources helps AI agents recommend you, not just AI search engines.

So what now? Start with machine-readability.

Here’s a practical starting point for any marketing manager:

1. Audit your site for machine-readability.

Can an AI agent parse your product data? Your pricing? Your specs? Your availability?

Use Google’s Rich Results Test or Schema Markup Validator. If your structured data is broken or missing, fix it. This is table stakes.

2. Think like an agent.

Ask ChatGPT or Claude to recommend products in your category. What does it say? What does it cite? What criteria does it use?

This gives you a rough sense of what agents prioritize. Is it price? Reviews? Features? Availability?

3. Structure your content for parsing, not just reading.

AI agents don’t read your beautiful brand story. They parse facts: pricing, features, specifications, availability, reviews.

Make this information explicit, structured, and easy to extract. FAQ sections. Comparison tables. Spec sheets. Product schema markup.

4. Don’t neglect the human journey.

Yes, optimize for agents. But remember: the human still approves. Brand trust, emotional resonance, and differentiation matter as much as ever.

The winning strategy is “AND,” not “OR.” Optimize for both journeys.

5. Monitor agent mentions (imperfectly).

Periodically ask various AI assistants about your category. Screenshot the results. Track whether you’re being recommended, and what’s being said about you.

It’s not a dashboard. It’s not perfect. But it’s better than flying blind.

The proof it works: HubSpot created a dedicated “AEO Pod” and focused on niche content and Reddit engagement (because ChatGPT has data licensing deals there). Result: 800% increase in AI assistant visibility and 1,400% increase in referral traffic from AI agents in 6-8 months.

That’s it for this prediction. Agree/disagree? Got remarks? Roast me in the comments.

Leave a comment

What’s next? The counter-trend nobody’s talking about.

Tomorrow: Prediction #4 — The “Human Premium” emerges.

Spoiler: As AI floods the internet and agents mediate decisions, “human-made” suddenly becomes scarce. And scarcity creates premium. The brands leaning into unscalable authenticity are winning.

Cheers, Kasper

I’ll admit: I started skeptical. “Optimizing for AI search” sounded like rebranded SEO with fancier acronyms. GEO. AEO. LLMO. Another gold rush for consultants.

Patrick Stox from Ahrefs even warns about “GEO grifters” selling snake oil.

But then I studied how the engines actually work. And I changed my mind.

Oh Kasper from 4 months ago, you were so naive.

Prediction 2/15: PR becomes the new SEO. Because the currency of discovery shifted from links to mentions.

What’s happening? We’re moving from “being found” to “being chosen.”

The hook stat you’ve probably seen: 58.5% of Google searches now end without a click. Up from 25% five years ago.

But here’s the stat that actually matters:

There’s only a 62% overlap between what ranks #1 on Google and what ChatGPT recommends.

Let that sink in. You can win SEO and lose AI search. They’re different games now.

The numbers:

• Organic CTR dropped from 28.5% (2023) to 17.9% (2025)

• HubSpot: 70-80% decline in organic traffic between 2024-2025 (here’s a pretty interesting about it on their own blog)

• But AI search visitors convert 4.4x higher than organic

• Ahrefs sees 23x higher conversion from AI referrals on their own site

Rand Fishkin, pretty much the godfather of SEO, put it bluntly:

“The currency of Google search was links. The currency of large language models is mentions—specifically, words that appear frequently near other words across the training data.”

Links vs. mentions. That’s the entire shift in one sentence.

And Ahrefs proved it with data. Their study of 75,000 brands found that Brand Web Mentions (just text, not even links) correlated 0.664 with AI visibility. Backlinks? Only 0.218. Mentions beat links by 3x.

What’s amplifying this? LLMs read the web differently than Google.

Here’s what most people miss: Google and LLMs don’t work the same way. At all.

Google is a ranking system. It counts backlinks, analyzes on-page signals, and sorts results by authority.

LLMs are pattern matchers. They learn from training data. If “Salesforce” appears next to “CRM” a million times across the web, the model learns that association as truth. No PageRank required.

Ethan Mollick, Co-Director of Generative AI Labs at Wharton confirms it:

“It doesn’t know the truth. It knows what looks like the truth based on the consensus of the internet.”

This is why PR became the lever. You can’t change what an LLM “believes” by tweaking your H1 tags. You only change it by getting mentioned repeatedly, positively, and in places the model trusts.

The ugly truth about GEO aka AEO aka AI Search aka LLMO aka…:

• If the New York Times, G2, and Reddit all agree your software is the best? The LLM outputs that as fact.

• If you’re not mentioned anywhere authoritative? You don’t exist to the model.

But here’s the frame that actually changed my thinking:

Traditional search gave you ten blue links. You optimized to be one of them. The user clicked, browsed, and chose.

AI search gives one synthesized answer. The AI already chose for them. If you’re not in that answer, you don’t exist.

Here’s an example I adore (and not just because it’s a Belgian company 🇧🇪):

Tally, the form builder, bootstrapped to $4M ARR. A significant piece of their growth? Generative Engine Optimization.

They documented their entire strategy publicly. The core insight: they focused on being mentioned in comparison articles, Reddit threads, and tool roundups—not just ranking their own pages. They played the mentions game, not the backlinks game. And it worked. Read more about their AI Search strategy here.

But there’s also something tactical happening. AI doesn’t read your page like you think.

1. It looks at your title and description first (like a human scanning search results)

2. It jumps to relevant sections (like doing CTRL+F)

3. It reads a few sentences above and below to gauge context

4. Then it decides if the page is worth ingesting

Your beautiful intro paragraph? The AI might skip it entirely.

Your structured, fact-dense section with the answer? That’s what gets cited.

What’s the catch? It’s not that big…

Here’s where I refuse to join the hype train. Because there’s a LOT of noise around this topic, and two camps have formed:

Camp 1: “AI search is basically the same as SEO.”

Camp 2: “SEO is dead, AI search replaced it.”

I’m in neither camp. Here’s the nuanced reality.

The traffic is still tiny.

Google handles 14 billion searches per day. ChatGPT (for actual search-intent queries)? About 37.5 million.

That makes Google roughly 373x bigger than AI search.

And here’s the kicker: 96% of websites receive zero traffic from AI search right now. Zero.

So yes, optimize for it. But don’t gut your Google strategy for something that’s currently two pixels wide on a pie chart.

The “black box” problem.

There are no reliable dashboards for AI visibility. No “AI Search Console.” No impression data. No ranking reports. You’re optimizing based on spot-checks and vibes.

Those who claim they can track it (like the bazillion “LLM Visibility Tools”), can all be wrong. Nobody know.

This makes measurement nearly impossible. You’re optimizing blind.

Black hat GEO is already here.

Just like early SEO had keyword stuffing and link farms, GEO already has manipulation tactics. People flooding forums with fake recommendations. Injecting hidden text. Spamming “Best X tools” listicles.

It’s called “LLM Poisioning”, and it’s actually easier than I thought.

Brings me back to the good ol days of keyword stuffing with white text on white backgrounds (IYKYK).

The silver lining nobody mentions.

Here’s the flip side: AI search traffic converts 4.4x higher than traditional organic traffic. Ahrefs saw 23x higher conversion for their own site.

Less traffic, but better traffic. The people who find you through AI search have high intent. They’re not browsing—they’re buying.

The foundations are the same (but the tactics aren’t).

Ok so here’s my actual position: Good content matters in both. Trust signals matter in both. Answering real questions matters in both.

But the mechanisms differ:

• Google counts backlinks → LLMs count mentions

• Google reads meta tags → LLMs read internet consensus

• Google ranks pages → LLMs synthesize answers

Same principles. Different playbooks.

What to do if you’re just starting in marketing?

SEO skills are FAR FROM DEAD. Technical SEO, content strategy, keyword research—these still matter for Google, which is still 99% of the game.

But you need to add PR skills to your stack. Learn how to get mentioned everywhere:

• Pitching journalists relevant news

• Building relationships with industry publications

• Guest posting on authoritative sites

• Engaging authentically on Reddit (which LLMs heavily weight because of licensing deals with OpenAI/Google)

The hybrid skill set is going to be extremely valuable: someone who can do technical SEO and digital PR.

Also: learn how to talk to AI. Not “prompt engineering” in the gimmicky sense, but understanding how LLMs read, parse, and prioritize content. That’s a real skill now.

So what now? Use AI to optimise for AI, duh.

Here’s a practical starting point for any marketing manager:

1. Ask AI for your “to-do list.”

Go to your chatbot of choice (we all know it’s Grok’s new Spicy mode). Ask it to recommend companies in your category. If you’re not listed, ask why.

The AI will literally tell you what’s missing: “You’re not mentioned in major industry publications,” or “I don’t see reviews on G2.”

It gives you a to-do list for free.

2. Map your “mention gaps.”

Where are your competitors being talked about that you’re not? Reddit threads. Industry newsletters. Comparison articles. Podcast appearances.

These are your PR targets.

But you can’t just publish generic content and expect mentions. LLMs prioritize unique value. Think original data, contrarian opinions, or unique insights that don’t exist elsewhere in the training set.

To earn mentions, you need to be the source of something new. Publish original research. Share first-party data. Take a specific stance that adds to the conversation.

Like this newsletter for example, amirite?

3. Optimize sections, not just pages.

Remember: ChatGPT doesn’t read top-to-bottom. It jumps to relevant sections. So:

• Lead each section with the key information

• Use clear, scannable headings

• Add unique data points (pages with 19+ data points get 5.4 citations on average vs. 3.2 for sparse pages)

• Kill the vague metaphors. LLMs can misinterpret creative language

4. Think entities, not keywords.

Old question: “What keywords should I rank for?” New question: “What associations should I build?”

You want the LLM to learn: [Your Brand] = [Your Category]. That association is built through mentions, not meta tags.

5. Make yourself machine-readable.

PR gets you mentioned. But there’s a technical bridge too: AI agents need to understand what you’re selling.

This means structured data. Schema markup. JSON-LD. Your product features, pricing, and specs must be machine-readable so AI agents can retrieve them accurately.

Gartner predicts traditional SEO and PPC will give way to Agent Engine Optimization (AEO). To succeed, products must be parseable by AI. If an agent can’t read your specs, it can’t recommend you.

6. Don’t abandon Google.

This is important. AI search is the future, but it’s not the present. 96% of sites get zero AI traffic. Google is still 373x bigger.

Do both. But recognize they’re different games now.

That’s it for this prediction. Agree/disagree? Got remarks? Roast me in the comments.

Leave a comment

What’s next? AI decides what we buy now.

Tomorrow: Prediction #3; AI becomes the gatekeeper standing between you and your customers.

Spoiler: 24% of consumers already use AI shopping assistants. And they’re not just gatekeepers—they’re becoming “Agents of Customers,” making buying decisions on behalf of humans.

Cheers, Kasper

Hey y’all, Kasper here. It’s been a while since my last newsletter. I was in full distraction-free mode building my new company Markomatic.

But I’m back in action, sharing my 15 predictions for marketing careers. Based on hundreds of hours gathering blogs, newsletters, videos, webinars, reports, and academic papers. Each post will be a short opinion piece with stats, quotes, and examples.

Prediction 1/15: Creators aren’t just a channel anymore. They’re the new operating system for content.

What’s happening? Trust in brand down, trust in faces up.

Let’s start with the uncomfortable reality: 74% of new web pages now contain AI-generated content. Your feed is drowning in synthetic noise. Parrot on a bike videos. AI Stephen Hawking explaining crypto. Slop everywhere.

Consumers don’t trust the AI madness. AI-generated Ads are getting canceled left and right.

So where did trust go? To faces.

Kieran Flanagan, HubSpot’s SVP of Marketing, put it bluntly:

“We are known as the inbound company. We generated a lot of demand from branded channels. Today we generate more demand from human-led channels—individuals creating content on YouTube, newsletters, podcasts—than we do from traditional brand-led channels.”

Read that again. HubSpot. The $30B+ inbound company. Now gets more demand from individuals than from their brand.

And they’re doubling down, launching a program where they invest millions in upcoming creators.

Read more about Hubspot’s strategy and why they bought “The Hustle”:

Your customers don’t trust your logo anymore. They trust faces. In a world of infinite AI content, “human” became a scarce commodity. Scarcity creates premium.

What’s amplifying this? AI gave creators superpowers.

A solo creator with the right stack can now outproduce your entire content team. Not because they’re better. Because they’re faster, cheaper, and audiences trust them more.

Case in point: Creative director Karen X Cheng partnered with Insta360. Instead of a standard product demo, she used AI to turn a walk through a doorway into trippy, animated art. 10M+ views. 50k likes. AI + human creativity > AI alone.

The numbers back this up:

• 98% of marketers already use creator content across channels

• Over 60% plan to boost creator partnerships next year

• 75% of enterprise B2B companies will increase influencer budgets in 2026 (Forrester)

• By 2026, 2/3 of B2B content will be created by employees OUTSIDE content teams (Forrester)

Neal Mohan, CEO of YouTube:

“Creators are the new startups of Hollywood.”

Adobe’s “Future of Creativity” report puts it simply:

“Creators are fueling the content engine, with non-professional creators publishing content weekly.”

What’s the catch? Trust, control and budget.

Here’s where I pump the brakes. Because the creator hype has some serious holes nobody wants to talk about.

The Rebrand Problem.

Let’s call it what it is: “Creator” is just “influencer” with better PR. We already learned to distrust influencers. Shameless promotion of stuff they don’t use. Fake authenticity at scale. Remember when we started hating them? That wasn’t long ago.

Calling them “creators” doesn’t fix the fundamental trust erosion. At some point, scale kills authenticity. We’re repeating history and pretending we’re not.

Honestly, I didn’t understand the difference at first but this article by NoGood explains it nicely.

The Control Paradox.

Every report says “cede control to creators.” Kantar’s exact words:

“Over-direct and the spark dies; under-brief and the brand risks disappearing.”

Great advice. But brands structurally CAN’T do this. Legal reviews. Compliance sign-offs. Brand guidelines. Ego. Most creator content dies in approval purgatory before it ever goes live. The advice is right. The execution is impossible for most organizations.

The Budget Hypocrisy.

Brands say “authenticity.” Budgets say “performance.” Economic pressure means tighter budgets, which means less appetite for betting on other people instead of owned media.

Good luck convincing the CFO to invest in some internet person creating viral videos.

Where does it fall flat? Boring companies.

Every sexy example is a tangible product. Cameras. Cosmetics. Consumer goods. But what about SaaS? Consulting? Insurance? Professional services?

The creator playbook has a massive gap nobody’s addressing. It’s easier when you can ship a physical, fun product to an influencer. Much harder when you’re selling boring stuff.

That said, it’s not impossible. It’s a matter of creativity. Gong turned all their employees into LinkedIn thought leaders. They call them “Gongsters.”

That’s B2B creator strategy without shipping a product.

Or look at PostHog: they sponsor engineers to build cool things using their tool. That’s the B2B version of an unboxing video. Call it Proof of Utility.

To be honest, I didn’t find many decent examples like these. But just get creative, OK?

What to do if you’re just starting in marketing?

Here’s a spicy take nobody asked for: If you’re 22 and entering marketing, maybe DON’T follow the traditional path.

Here’s why. Junior marketers used to learn by doing the grunt work. Writing social posts. Editing images. Drafting emails. That repetition built taste and judgment.

AI now does 95% of this “middle layer” work. And brands aren’t hiring juniors to create anymore, they’re paying external creators instead.

This creates what I call the “Apprenticeship Gap.” No path for new talent to develop the taste required to become a strategist.

So here’s my contrarian career advice: Follow the budget, not the job title.

If brands are shifting spend to creators, maybe the smart move is to become the creator that brands pay. Build your own audience. Learn the craft from the creator side. The apprenticeship path is dying. The creator path is wide open.

And yes, this is uncomfortable advice because it’s not really a job with steady pay. So here’s a video to get you started.

So what now?

Despite all the caveats, the shift is real. Ignoring it isn’t an option. So here’s what you actually can do as a marketing manager.

A practical starting point: Take 5% of your paid advertising budget and give it to creators specifically to create ad assets. Test creator-produced creatives against your agency-produced ones. See what wins.

Follow this highly simplified plan:

1. Set the guardrails: Define what the brand can’t compromise on. Keep it short.

2. Provide the raw materials: Assets, sounds, characters, products. Make it easy to remix.

3. Cede control: To the humans your customers actually trust. Then get out of the way.

Or join the dark side and become the creator. Your choice!

That’s it for this prediction. Agree/disgree? Got remarks? Roast me in the comments.

Leave a comment

What’s next? SEO is (not) dead.

Tomorrow: Prediction #2 — Why your SEO strategy just became obsolete.

Spoiler: 58.5% of Google searches now end without a click. And it’s not just “zero click,” it’s “zero click, satisfied by AI.”

Cheers, Kasper

Each week, I’ll give you a zero-fluff, bullshit-free newsletter with the most important:

• 🧠 Things to know: distilled insights, news, trends, and stats that make you sound smart

• 👀 Things to see: handpicked posts, news, video tutorials and spicy takes that matter

• 🧪 Things to try: experiment with tools, prompts, workflows, and weird hacks

It’s the perfect read while taking a 💩 at the office. Let’s go.

Subscribe now

Things to know

Spicy stats and facts to drop in your next marketing meeting

🧠 Websites using AI-written articles grow 5% faster. Oh and 65% of marketers believe human content is better quality than AI content, while human content is 4% more likely to be negatively affected.
Read the full Ahrefs report with more juicy stats

🧠 People screaming “AI will replace your job!” are actually just tech companies trying to shove their product down your throat. You’re not reading news, you’re reading ads. Don’t panic, you’re safe.
Read the full thesis by Rand Fishkin

🧠 Why pay a full-time CMO when a fractional one can coordinate your agents and GPTs a few days a month? Hire bots for hands, rent the brain part-time, save the budget.
Read the opinion (with a grain of salt)

Things to see

Content you’ll read instead of hoarding it in the tab graveyard

👀 AI-generated video ad with $2.000 budget airs during the NBA Finals. Goodbye, creative agency fees.
Watch the video and see the future

• Betting platform Kalshi hired one “AI filmmaker” to crank out a 30-sec TV spot with Google Veo 3 in two to three days.

• Cost: ≈ $2,000 → a 95 % price drop versus a traditional production crew.

• Workflow: Gemini for shot list —> Veo for clips —> CapCut for edits

👀 AI-generated answers are stealing +70% of your clicks. Here’s how to make the bot cite you instead. (Kevin Indig and Wynter)
Watch the full video workshop

• Before AI: focus on clicks to your site. After AI: be the expert the AI quotes.

• Chunk your content. Match every AI section (price, specs, pros) with small paragraphs.

• Publish data stories, not gated PDFs. Original stats = citation bait for AI.

👀 The AI-Search Content-Optimization Checklist. AKA “How to rank in ChatGPT instead of crying about lost clicks”. (Aleyda)
Open the Google Sheet and save a copy

• One Google Sheet. Zero SEO guesswork. Feed it to your AI tool of choice.

• Hits every bot trigger: Q&A blurbs, tight TL;DRs, schema, inline receipts…

• Quick wins: quote your own data, drop FAQ-JSON, add “According to our 2025 study…”.

Things to try

Tools that make you look like a genius before the others catch up

🧪 Dalton: Turn your site into a 24/7 automated CRO machine — no devs, no waiting
(Freemium with free scan)

• Dalton scans your pages and queues A/B test ideas in under 5 min.

• You click ✅ or ❌ on copy, CTA, layout tweaks.

• Plugs into Shopify, Webflow, WordPress, whatever.

🧪 Mikrolo Smart: Get reports on GA4 + Google Ads anomalies and campaign health
(Starts at $19/m)

• Get instant “WTF just happened?” alerts when something breaks.

• One-click plug-in for GA4 + Google Ads

• Weekly reports tell you what broke and how to fix it

🧪 Recraft: Interactive AI artboard for logos, ads, mock-ups, and vectors (freemium)

• Generate a plethora of on-brand images

• Get pixel AND vector outputs you can actually drop into Figma

• Built-in styles: 3D icons, illustrations, seamless patterns, stock photos

That’s it for this week. Go drop it in Slack and watch six people pretend they already knew.

Cheers,

Kasper, The Artificial Marketeer

Each week, I’ll give you a zero-fluff, bullshit-free newsletter with the most important:

• 🧠 Things to know: distilled insights, news, trends, and stats that make you sound smart

• 👀 Things to see: handpicked posts, news, video tutorials and spicy takes that matter

• 🧪 Things to try: experiment with tools, prompts, workflows, and weird hacks

It’s the perfect read while taking a 💩 at the office. Let’s go.

Subscribe now

Things to know

Spicy stats and facts to drop in your next marketing meeting

🧠 Unicorn startup Builder.ai faked it ‘til they bankrupted. Their “AI” was actually 700 Indian devs pretending to be a bot. Natasha The Bot, to be specific.
Read the full trainwreck

🧠 Google’s AI Overviews are wrong about 2% of the time but cause a 60% drop in traffic for publishers. Your SEO strategy is now a piñata.
See the damage

🧠 CMOs are betting $10M on AI, and only 8% still think it’s hype. Optimism is up, anxiety is down. AI's moving from experiment to budget line item.
See the full BCG research

Things to see

Content you’ll read instead of hoarding it in the tab graveyard

👀 The 9 brutal truths about AI’s impact on B2B marketing (Pierre Herubel)
Read the full essay

• Legacy brands still figuring out Instagram will get crushed by AI-native marketeers

• AI agents will soon run your entire tool stack

• Building an audience is more important than building product

👀 How to get your marketing team to stop talking about AI and actually use it… In a one-day hackathon (MKT1)
Get the guide

• Full playbook to run your first internal AI hackathon

• Get your team experimenting with Clay, Lovable, Replit, Figma Make

• Step-by-step breakdown with examples: prep, build, demo, repeat

👀 How to automate Facebook Ads with AI (Alex Cooper)
Watch the tutorial (60min)

• Full walkthrough on AI-powered Facebook Ads

• Reddit comment mining with Gigabrain + persona analysis via Deep Research

• Ad copywriting prompts for Claude

Things to try

Tools that make you look like a genius before the others catch up

🧪 Moonlit Platform: Automate 90% of your SEO content workflows. Like Make or N8N, but designed for marketers. (Freemium but affordable)

• Step-by-step builder for briefs, visuals, meta tags

• Templates like “Generate SEO Brief” & “Add visuals to post.”

• No dev skills needed

🧪 Glims: Create scroll-stopping video reels in minutes. Perfect for campaigns, product launches, or that “we went to Lisbon” team offsite. (Freemium but very cheap)

• Drag and drop photos to make highlight reels

• Multi-format output for every platform

• Extremely budget-friendly

🧪 LLM SEO Monitor: Find out what ChatGPT, Gemini, and Claude are recommending. Are you winning the AI search wars? (Free)

• Type a query, see what the models rank you (and competitors) for

• Great for competitive intel & reverse-engineering AI logic

• Use it to get approval on your GEO budget

That’s it. You’re now officially 97% smarter than the LinkedIn bro writing “10 ChatGPT prompts that will blow your mind.”

Cheers,

Kasper, The Artificial Marketeer